queue-advisor-pricing-app
Compare SQS, Kinesis, EventBridge and MSK costs before committing to an AWS queue.
git clone https://github.com/fernandofatech/queue-advisor-pricing-app.gitQueueAdvisor is an interactive cost and fit calculator for AWS's primary messaging services — SQS, Kinesis, EventBridge, and MSK — built with Next.js and TypeScript, aimed at architects who need to make messaging decisions grounded in throughput, retention, and actual pricing.
Why I built this
Every time I start a new event-driven project, the same conversation happens: the client wants to know whether to use SQS, Kinesis, EventBridge, or MSK. The right answer depends on concrete variables — messages per second, retention window, replay requirements, consumption pattern (pull vs. push), and projected monthly cost. Doing that calculation manually in a spreadsheet is slow and error-prone; explaining it verbally to a non-technical stakeholder is even harder.
QueueAdvisor addresses this directly: you provide your throughput and retention requirements, and the tool projects estimated costs for each service side by side, with guidance on which best fits your use case. It is not a replacement for the official AWS Pricing Calculator, but it is a decision accelerator — particularly useful in architecture workshops, FinOps reviews, and onboarding sessions for teams still learning AWS messaging pricing models.
The project is public, running in production at queue.moretes.com, and is part of my solutions architecture portfolio under the moretes.com ecosystem.
What the tool does
How it works internally
The project follows a modular structure oriented around the Next.js App Router (or Pages Router, depending on the active version). Pricing logic is encapsulated in TypeScript modules that model the cost dimensions of each service:
- SQS: cost per request (Standard and FIFO), differentiated by queue type.
- Kinesis Data Streams: cost per shard-hour and per PUT payload unit, sensitive to throughput and extended retention windows.
- EventBridge: cost per event published to custom event buses, distinguishing first-party from partner events.
- MSK: cost per broker-hour, storage, and data transfer — the most complex to estimate, which is reflected in the tool's guidance.
All calculations run entirely on the client (no external API calls at runtime), keeping latency at zero and eliminating backend dependencies. The UI accepts user parameters, passes them through the calculation modules, and renders comparative results. Deployment is via Vercel with continuous integration from the GitHub repository, making every push to the main branch an automatic production update.
Application flow
The user interacts with the Next.js UI in the browser; all calculation logic runs client-side. Deployment is managed by Vercel from the GitHub repository.
- Architect · / User
- Next.js UI · Input Form
- Pricing Modules · TS (SQS/Kinesis/EB/MSK)
- Results View · Side-by-side
- Vercel Edge · Hosting / CDN
- GitHub Repo · main branch
Local installation and usage
- 1
Prerequisites
Node.js 18+ and pnpm installed. If you use npm or yarn, substitute
pnpmin the commands below — the project does not document a lock file for another package manager. - 2
Clone the repository
Run
git clone https://github.com/fernandofatech/queue-advisor-pricing-app.gitand enter the directory withcd queue-advisor-pricing-app. - 3
Install dependencies
Run
pnpm install. pnpm will resolve the Next.js, Tailwind CSS, and TypeScript dependencies declared inpackage.json. - 4
Start the development server
Run
pnpm dev. The application will be available athttp://localhost:3000. No required environment variables are documented — the app runs without additional configuration. - 5
Production build (optional)
Run
pnpm buildto generate the optimized bundle, thenpnpm startto serve it locally. For deployment, connect the repository to Vercel — the project is already configured for automatic deployment via GitHub integration.
# 1. Clone
git clone https://github.com/fernandofatech/queue-advisor-pricing-app.git
cd queue-advisor-pricing-app
# 2. Install dependencies
pnpm install
# 3. Run in development mode (http://localhost:3000)
pnpm dev
# 4. (Optional) Production build
pnpm build
pnpm startTry the production version first
If you just want to explore the tool, go directly to https://queue.moretes.com. Cloning the repository makes sense if you want to adapt the pricing models, adjust calculation parameters for your AWS region, or integrate the logic into another project.
Frequently asked questions
Are prices automatically synced with AWS?
No. Reference values are hardcoded in the TypeScript modules and must be updated manually when AWS changes its pricing. Always verify against the official AWS Pricing Calculator for production decisions.
Does the tool cover all AWS regions?
The README does not specify multi-region support. Calculations likely use us-east-1 reference pricing. For other regions, cost multipliers may differ — treat results as relative estimates, not absolute figures.
Can I use this project as a base for my own calculator?
Yes. The project is MIT-licensed. You can fork it, adapt the pricing models, and publish your own version. Open an issue before submitting significant PRs.
Is MSK covered with the same level of detail as SQS?
Likely not with the same granularity. MSK's cost model is significantly more complex (broker-hours, storage, data transfer, instance type). The tool provides guidance and estimation, but MSK requires deeper analysis for production sizing.
Who this project is for
QueueAdvisor is useful for solutions architects and platform engineers who need to quickly compare cost trade-offs between SQS, Kinesis, EventBridge, and MSK without opening four AWS documentation tabs simultaneously. It is particularly practical in architecture workshops, FinOps reviews, and early client conversations about event-driven system design. It does not replace the official AWS Pricing Calculator or a detailed sizing analysis for production workloads — the prices are hardcoded references that age. But as a fast decision tool and portfolio material demonstrating command of the AWS messaging space, it serves its purpose well. If you work with data architecture or event-driven systems on AWS and want an interactive visual reference to guide discussions, both the production version and the source code are worth exploring.